{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,16]],"date-time":"2026-09-16T05:04:11Z","timestamp":1789535051195,"version":"build-2803163510"},"reference-count":34,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2026,9,14]],"date-time":"2026-09-14T00:00:00Z","timestamp":1789344000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Liaoning Province Science and Technology Program Project","award":["2026JH2\/101390010"],"award-info":[{"award-number":["2026JH2\/101390010"]}]},{"name":"Liaoning Provincial Department of Education Science and Technology Innovation Team Project","award":["LJ222510144001"],"award-info":[{"award-number":["LJ222510144001"]}]},{"name":"Xingliao Talent Plan","award":["XLYC2202013"],"award-info":[{"award-number":["XLYC2202013"]}]},{"DOI":"10.13039\/501100005047","name":"Natural Science Foundation of Liaoning Province","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100005047","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This paper aims to address image degradation caused by adverse weather conditions and partial occlusion in autonomous driving scenarios. The network adopts a dual-branch architecture, which utilizes a residual fusion block (ResFuse) to achieve the deep fusion of cross-modal features. A dual-path attention mechanism (DualAtt) and an integrated high-frequency attention module (HFAtt) were designed to capture key information in feature maps. Additionally, this study designs a spatial-channel downsampling module (SCDown). This module implements spatial-to-channel image downsampling. Experimental results demonstrate that the proposed network achieves a detection speed of 61 frames per second (FPS) and precision (P) of up to 87.4% on the M3FD dataset. Comparative experimental results show that MHF-Net achieves 84.3% in the mAP50 evaluation metric. Compared to the baseline model, the number of parameters was reduced by 95% and the computational complexity was reduced by 88%. Compared with other mainstream object detection algorithms, MHF-Net strikes a favorable balance regarding performance in autonomous driving scenarios.<\/jats:p>","DOI":"10.3390\/s26185816","type":"journal-article","created":{"date-parts":[[2026,9,14]],"date-time":"2026-09-14T10:19:41Z","timestamp":1789381181000},"page":"5816","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["MHF-Net: Multi-Modal Residual Fusion Object Detection Network Based on High-Frequency Gated Convolution"],"prefix":"10.3390","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-7969-5895","authenticated-orcid":false,"given":"Bailin","family":"Chen","sequence":"first","affiliation":[{"name":"School of Information Science and Engineering, Shenyang Ligong University, Shenyang 100159, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"methodology","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"},{"role":"investigation","vocabulary":"credit"},{"role":"validation","vocabulary":"credit"},{"role":"project-administration","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3839-3965","authenticated-orcid":false,"given":"Bo","family":"Qian","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering, Shenyang Ligong University, Shenyang 100159, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"methodology","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"},{"role":"funding-acquisition","vocabulary":"credit"},{"role":"project-administration","vocabulary":"credit"},{"role":"investigation","vocabulary":"credit"},{"role":"supervision","vocabulary":"credit"}]}],"member":"1968","published-online":{"date-parts":[[2026,9,14]]},"reference":[{"key":"ref_1","unstructured":"Zou, Z., Chen, K., Shi, Z., Guo, Y., and Ye, J. 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